Barrier and guardrail detection using a single camera

ABSTRACT

Driver assistance systems for detecting a structural barrier extending along a road. The driver assistance system may be mountable in a host vehicle. The camera may capture multiple image frames in the forward field of view of the camera. A processor may process motion of images of the barrier in the image frames. The camera may be a single camera. The motion of the images may be responsive to forward motion of the host vehicle and/or the motion of the images may be responsive to lateral motion of the host vehicle.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/012,455, filed Feb. 1, 2016, which is a continuation application ofU.S. application Ser. No. 13/237,163, filed Sep. 20, 2011, now issued asU.S. Pat. No. 9,280,711, which claims the benefit of U.S. ProvisionalPatent Application No. 61/385,122, filed Sep. 21, 2010, the entirecontents of which are incorporated herein by reference.

BACKGROUND 1. Technical Field

The present disclosure relates to driver assistance systems andparticularly to a method for detection along a road traveled by avehicle, the presence of a guard rail or a vertical lane divider using acamera and, more particularly to estimate the lateral distance to theguard rail or the concrete lane divider.

2. Description of Related Art

During the last few years camera based driver assistance systems (DAS)have been entering the market; including lane departure warning (LDW),automatic high-beam control (AHC), traffic sign recognition (TSR) andforward collision warning (FCW).

Lane departure warning (LDW) systems are designed to give a warning inthe case of unintentional lane departure. The warning is given when thevehicle crosses or is about to cross the lane marker. Driver intentionis determined based on use of turn signals, change in steering wheelangle, vehicle speed and brake activation. There are various LDW systemsavailable. One algorithm for lane departure warning (LDW) used by theApplicant/assignee (Mobileye Technologies Ltd., Nicosia, Cyprus,hereinafter “Mobileye”) of the present application is predictive in thatit computes time-to-lane crossing (TLC) based on change in wheel-to-lanedistance and warns when the time-to-lane crossing (TLC) is below acertain threshold. Other algorithms give a warning if the wheel isinside a certain zone around the lane marker. In either case, essentialto the lane departure warning system is the lane marker detectionalgorithm. Typically, the lane markers are detected in the camera imageand then, given the known camera geometry and camera location relativeto the vehicle, the position of the vehicle relative to the lane iscomputed. The lane markers detected in the camera image are thencollected over time, for instance using a Kalman filter. Wheel-to-lanemarker distance may be given with an accuracy of better than 5centimeters. With a forward looking camera, wheel-to-lane markerdistance is not observed directly but is extrapolated from the forwardview of the camera. The closer road markings are observed, lessextrapolation is required for determining wheel-to-lane marker distanceand more accurate estimates of wheel-to-lane marker distance areachieved especially on curves of the road. Due to the car hood and thelocation of the camera, the road is seldom visible closer than sixmeters in front of the wheels of the car. In some cars with longerhoods, minimal distance to visible road in front of the car is evengreater. Typically the lane departure warning system of Mobileye workson sharp curves (with radius down to 125 m). With a horizontal field ofview (FOV) of 39 degrees of the camera, the inner lane markers are stillvisible on curves with a radius down to 125 meters. In order tocorrectly perform lane assignment on curves, lane markings are detectedat 50 meters and beyond. With a horizontal field of view (FOV) of 39degrees for the camera, a lane mark of width 0.1 meters at 50 m distancecorresponds in the image plane to just under two pixels wide and can bedetected accurately. The expectation from the lane departure warningsystems is greater than 99% availability when lane markings are visible.Expectation with 99% availability is particularly challenging to achievein low light conditions when the lane markings are not freshly painted(have low contrast with the road) and the only light source is the carhalogen headlights. In low light conditions, the lane markings are onlyvisible using the higher sensitivity of the clear pixels (i.e. using amonochrome sensor or a red/clear sensor). With the more powerful xenonhigh intensity discharge (HID) headlights it is possible to use astandard red green blue (RGB) sensor in most low light conditions.

The core technology behind forward collision warning (FCW) systems andheadway distance monitoring is vehicle detection. Assume that reliabledetection of vehicles in a single image a typical forward collisionwarning (FCW) system requires that a vehicle image be 13 pixels wide,then for a car of width 1.6 m, a typical camera (640×480 resolution and40 deg FOV) gives initial detection at 115 m and multi-frame approval at100 m. A narrower horizontal field of view (FOV) for the camera gives agreater detection range however, the narrower horizontal field of view(FOV) will reduce the ability to detect passing and cutting-in vehicles.A horizontal field of view (FOV) of around 40 degrees was found byMobileye to be almost optimal (in road tests conducted with a camera)given the image sensor resolution and dimensions. A key component of atypical forward collision warning (FCW) algorithm is the estimation ofdistance from a single camera and the estimation of scale change fromthe time-to-contact/collision (TTC) as disclosed for example in U.S.Pat. No. 7,113,867.

A recent U.S. Pat. No. 7,411,486 states (column 1, lines 35-37) thatlane-departure warning systems which are equipped with only oneimage-transmitting sensor are not capable of differentiating betweenedge-of-lane markings and a structural boundary at the edge of the lane.(emphasis added) Consequently, U.S. Pat. No. 7,411,486 discloses adriver assistance system for warning a driver of a motor vehicle of arisk of departure from the lane. The disclosed system includes a camerafor detecting edge-of-lane and/or lane markings in the area sensed bythe camera, and in addition a distance sensor with which the distancefrom objects elevated with respect to the surface of the lane can bedetermined in the region of the edge of the lane, in particular of astructural boundary of the edge of the lane.

Thus there is a need for and it would be advantageous to have a driverassistance system and corresponding method adapted to perform andvertical structural barrier or guardrail detection along the edge of theroad or a lane using a camera and without requiring use of an additionalsensor for instance to detect distance to the guardrail or barrier.

BRIEF SUMMARY

Various methods are disclosed herein for detecting a structural barrierextending along a road. The methods are performable by a driverassistance system mountable in a host vehicle. The driver assistancesystem may include a camera operatively connected to a processor.Multiple image frames may be captured in the forward field of view ofthe camera. In the image frames, motion of images of the barrier areprocessed to detect the barrier. The camera may be a single camera. Themotion of the images may be responsive to forward motion of the hostvehicle and/or the motion of the images may be responsive to lateralmotion of the host vehicle.

The structural barrier may include multiple posts. Multiple linear imagestructures are hypothesized in an image frame as projections of thebarrier onto the road surface and multiple vertical image coordinatesare obtained respectively from the linear image structures. The linearimage structures may be image lines which run parallel to the image ofthe road and intersect the vanishing point of the image of the lanemarkers.

Multiple forward distances and corresponding lateral distances to theposts are computed based on the vertical image coordinates. Based on theknown forward motion of the host vehicle and horizontal imagecoordinates of the linear image structures new horizontal imagecoordinates of the linear image structures are computed. The horizontalimage coordinate in a second image frame of one of the images of thelinear image structures is selected to align an image of one of theposts.

Alternatively, for each of the posts, forward distances from the hostvehicle to the posts may be determined based on the motion of the imagesand the forward motion of the host vehicle. Lateral distances to theposts from the host vehicle may be determined from the forward distancesand the horizontal image coordinates of the posts. Road plane lines atthe lateral distances may be hypothesized to form multiple hypothesizedroad plane lines as projections of the vertical structural barrier ontothe road surface. The hypothesized road plane lines at the lateraldistances may be projected onto an image of the vertical structuralbarrier in an image frame. The correct road plane line is selected fromthe hypothesized road plane lines by aligning the correct road planeline with the image of the vertical structural barrier in the imageframe.

Alternatively for a barrier without substantial vertical image texture,an image patch may be located in one of the image frames on an imageline intersecting the vanishing point in the image frame. The imagepatch may be warped based on a vertical surface model. The verticalstructural barrier may be detected by ascertaining that the patch is animage of the vertical structural barrier when points in columns of thepatch scale vertically with host vehicle motion. Alternatively, theimage patch may be warped based on a road surface model, and the patchmay be an image of the road surface when points in rows of the patchscale horizontally with host vehicle motion.

Various driver assistance systems may be provided for detecting astructural barrier extending along a road, The driver assistance systemmay be mountable in a host vehicle. The camera may capture multipleimage frames in the forward field of view of the camera. A processor mayprocess motion of images of the barrier in the image frames. The cameramay be a single camera. The camera may be configured to view in thedirection of forward motion of the host vehicle. The motion of theimages may be responsive to forward motion of the host vehicle and/orthe motion of the images may be responsive to lateral motion of the hostvehicle.

The motion of the images of the structural barrier may correlate with animage line in the direction of the vanishing point of the road, whereinthe image line corresponds to a vertical projection of the structuralbarrier onto the road plane.

The processor may be operable to hypothesize linear image structures asprojections of the structural barrier onto the road plane to producemultiple hypotheses. Each of the hypotheses gives a lateral position ofthe barrier relative to the host vehicle. For each hypothesis, thelateral positions and host vehicle motion are used to predict imagemotion. The predicted image motion is compared to the actual imagemotion to verify the hypothesis and to derive the actual lateralposition of the structural barrier relative to the host vehicle.

Motion of the host vehicle may have a lateral component relative to theroad direction and the image motion is of an image line in the imagethat is above the linear image structure The image line may be that ofthe top of the barrier. Vertical motion or looming of the image line maybe used to determine lateral distance between the host vehicle and thestructural barrier to determine whether the image line is of the samelateral distance as the linear image structure (the barrier) or on theroad surface farther away.

The processor may be operable to hypothesize multiple linear imagestructures in an image frame as projections of the barrier onto the roadsurface and obtain thereby multiple vertical image coordinatesrespectively from the linear image structures. The processor may beoperable to compute multiple forward distances and corresponding lateraldistances to the posts based on the vertical image coordinates. Based onthe known forward motion of the host vehicle and horizontal imagecoordinates of the linear image structures, the processor may beoperable to compute new horizontal image coordinates of the linear imagestructures to select the horizontal image coordinate in a second imageframe of one of the images of the linear image structures and to alignan image of one of the posts.

Alternatively, for each of the posts, the processor may be operable todetermine forward distances from the host vehicle to the posts based onthe motion of the images and the forward motion of the host vehicle. Theprocessor may be operable to compute lateral distances to the posts fromthe host vehicle from the forward distance and horizontal imagecoordinates x of the posts. The processor may be operable to hypothesizeroad plane lines at the lateral distances, to form multiple hypothesizedroad plane lines as projections of the structural barrier onto the roadsurface; to project the hypothesized road plane lines at the lateraldistances onto an image of the structural barrier in an image frame. Theprocessor may be operable to select the correct road plane line from thehypothesized road plane lines by aligning the correct road plane linewith the image of the structural barrier in the image frame.

Alternatively for a barrier without substantial vertical image texture,the processor may be operable to locate in one of the image frames animage patch on an image line intersecting the vanishing point in animage frame, to warp said image patch based on a vertical surface modeland to detect the structural barrier by ascertaining that the patch maybe an image of the structural barrier when points in columns of thepatch scale vertically with host vehicle motion. Or, the processor maybe operable to ascertain that the patch may be an image of the roadsurface if or when points in rows of the patch scale horizontally withhost vehicle motion.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention is herein described, by way of example only, withreference to the accompanying drawings, wherein:

FIGS. 1 and 2 which illustrate a system including a camera or imagesensor mounted in a vehicle, according to an aspect of the presentinvention.

FIG. 3 shows a road scene according to an aspect of the presentinvention.

FIG. 4 illustrates a simplified generalized method, according to aspectsof the present invention.

FIGS. 5a and 5b illustrates matching of images of a vertical post of aguard rail to a number of similar images in a second image frame,according to an aspect of the present invention.

FIGS. 6a and 6b illustrates forward viewing images frames of road scenesincluding features of the present invention.

FIG. 6c includes a flow diagram of a method according to an aspect ofthe present invention using the image frames of FIGS. 6a and 6 b.

FIG. 6d includes a flow diagram of another method according to an aspectof the present invention using the road scenes of FIGS. 6a and 6 b.

FIGS. 7a and 7b forward viewing images frames of road scenes includingfeatures of the present invention, and

FIG. 7c is a flow diagram illustrating yet another method according toan aspect of the present invention.

DETAILED DESCRIPTION

Reference will now be made in detail to embodiments of the presentinvention, examples of which are illustrated in the accompanyingdrawings, wherein like reference numerals refer to the like elementsthroughout. The embodiments are described below to explain the presentinvention by referring to the figures.

Before explaining embodiments of the invention in detail, it is to beunderstood that the invention is not limited in its application to thedetails of design and the arrangement of the components set forth in thefollowing description or illustrated in the drawings. The invention iscapable of other embodiments or of being practiced or carried out invarious ways. Also, it is to be understood that the phraseology andterminology employed herein is for the purpose of description and shouldnot be regarded as limiting.

By way of introduction, embodiments of the present invention may bedirected to detection of guard rails and/or other generic structuralbarriers by image processing using a monochromatic camera which may bededicated to multiple driver assistance systems or functions runningsimultaneously and/or in parallel in a host vehicle. The use of anothersensor, (e.g. time-of-flight laser distance sensor or a second camera)other than a single camera may be avoided, to sense the presence of astructural barrier extending along the edge of the road. The camera maybe mountable behind the windshield with the optical axis of the camerasubstantially parallel to the forward direction (Z) of motion of thehost vehicle so that the camera may be forward viewing.

The term “structural barrier” as used herein is a road barrier installedand extending along a road at the side of a road, at the median of adivided highway or as a lane divider. The structural barrier may be aconcrete barrier, Jersey barrier, a metal guard rail or a cable barrier.The concrete barrier may include anti glare slats on top as disclosed inU.S. Pat. No. 5,181,695. The terms “structural barrier” and “verticalstructural barrier” are used herein interchangeably.

The term “posts” as used herein refers to an imageable vertical texturein a structural barrier and may include any vertical structure orsurface texture, e.g painted stripes, or the anti-glare slats. Hence,The terms “vertical texture” and “post” are used herein interchangeably.

Reference is now made to FIGS. 1 and 2 which illustrate a system 16including a camera or image sensor 12 mountable in a vehicle 18,according to an aspect of the present invention. Image sensor 12,imaging a field of view in the forward direction typically deliversimages in real time and the images may be captured in a time series ofimage frames 15. An image processor 14 may be used to process imageframes 15 simultaneously and/or in parallel to serve a number of driverassistance systems. Image sensor 12 is typically monochrome orblack-white, i.e. without color separation. By way of example in FIG. 2,image frames 15 may be used to serve a warning system 23 which mayinclude collision warning 17, lane departure warning 19, traffic signrecognition (TSR) 21 and barrier and guard rail detection 22 (BGD).Image processor 14 is used to process image frames 15 to detect barriersand/or guardrails in the forward field of view of camera 12. The terms“camera” and “image sensor” are used herein interchangeably.

The detection of guard rails, structural barriers, e.g. concrete lanedividers is important for many driver assistance functions. Aspects ofthe present invention may include exchange of information betweenbarrier and/or guardrail detection 22 and other driver assistancefunctions and/or systems including but not limited by FCW 17 and LDW 19.For example, a Lane Departure Warning (LDW) 19 as part of warning system23, may respond more strongly to a lane departure towards a guard railor a barrier rather than a lane marker or even a white line. A ForwardCollision Warning (FCW) system 19 may trigger sooner if the path toeither side of in-path vehicle is blocked by a guard rail or anothervehicle.

The term “object” as used herein refers to an object in real space beingviewed by a camera. A guard rail along the edge of a road and a lanemarker in the road are examples of objects. The term “image” refers tothe image of one or more objects in image space at the focal plane ofcamera 12. Image coordinates (x,y) in small letters refer to image spaceand may be in arbitrary units or numbers of picture elements in thehorizontal and vertical directions with the pixel dimensions assumed.The term “image motion” refers to motion of an image of an object inimage space. From image frame 15 to a subsequent image frame 15 thepoints of the image of the object may map from one set of coordinates(x1,y1) to a different set of coordinates (x2,y2). The term “imagemotion” refers to the mapping of coordinates of an image from imageframe to image frame or a function of the mapping. The term “projection”or “projecting” as used herein refers to camera or perspectiveprojection unless otherwise indicated by the context.

FIG. 4 illustrates a simplified generalized method, according to aspectsof the present invention. The term “capture” as used herein refers tothe real time recording and/or storage of image frames 15 in memory, forexample volatile and/or non-volatile memory accessible by processor 14.In step 401, image frames are captured by camera 12 and in step 403 theimage motion of guardrails and/or structural barriers along the edge ofthe road may be processed while host vehicle 18 is moving on the road.

Reference is now made to FIG. 3 which shows an image frame 34 of a roadscene as viewed through the windshield of host vehicle 18 by camera 12,according to aspects of the present invention. Real space coordinates(X,Y,Z) usually in meters are indicated using capital letters. DistanceZ from camera 12 or from the front of vehicle 18 is in the forwarddirection of motion of vehicle 18. Lateral distance X is in the plane ofthe road perpendicular to forward direction. Host vehicle 18 may be fastapproaching an in-path target vehicle 36 ahead. The lane on the right ofvehicle 36 may be blocked by another vehicle 38. The exact location ofroad divider or barrier 30 on the left may be important to determine ifthere is an open path on the left. Image frame 34 shows two examples ofstructural barriers; mixed concrete and metal barrier 30 on the left anda solid concrete barrier 32 on the far right. A dominant texture onconcrete barrier 32 is parallel to the road so it may be a challenge inimage 34 to distinguish between structural barrier 32, a marking on theroad or a change of road surface color. A relevant issue with respect tothe dominant texture on concrete barrier 32, would be to assess if thereis a free emergency lane or shoulder to the right of vehicle 38 or doesbarrier 32 start already on or near white line 39. An observation ofbarrier 30 shows a vertical texture or posts 30 a. The repetitivepattern of the vertical texture may be detected. The vertical texturemay be distinguished from the road surface, however there still may be achallenge to estimate a lateral distance to barrier 30 because thebottoms of posts 30 a in barrier 30 do not necessarily reach the roadsurface. Estimating the lateral distance X between vehicle 18 andbarrier 30 based on the assumption that posts 30 a do reach the road maylead to a significant error in measurement of the lateral distance tobarrier 30. For example, if the bottom of post 30 a touches the road atcircle A, distance Z of 11.2 meter is given from host vehicle 18 andthen lateral distance X to barrier 30 is determined to be 3.13 meter tohost vehicle 18. If the bottom of post 30 a touches the road at circleB, a distance Z of 7.6 m is given and the barrier is 2.12 m lateraldistance X to the left of vehicle 36. Additionally, motion aliasing, dueto the repetitive pattern of the vertical texture may result in anambiguous computation of lateral position X of barrier 30. FIGS. 5a and5b show motion aliasing or how post 30 a in FIG. 5a may be matched to anumber of similar posts 30 a in a second image frame shown in FIG. 5b .Each possible post 30 a in the second image translates to a differentlateral distance X.

Reference is now made to FIGS. 6a and 6b which show

dz=dt*V=horizontal image co-ordinate of a post 30 a.

f=focal length of camera 12

y1={271, 310, 333, 353}=possible hypotheses of image verticalcoordinates possibly corresponding to road surface in image 60 a

Z1=f*H/(y1−yO)=distance Z

Z2=Z1−dz

X1=Z1*(x1−x0)/f=lateral distance X

X2=X1; new lateral distance X2

$\begin{matrix}{{x\; 2} = {{f*X\;{2/Z}\; 2} + {x\; 0\mspace{14mu}{new}\mspace{14mu}{horizontal}\mspace{14mu}{image}\mspace{14mu}{coordinate}\mspace{14mu}{of}}}} \\{{post}\mspace{14mu} 30a} \\{= {\left\{ {123,103.5,90,76} \right\} = {{possible}\mspace{14mu}{projections}\mspace{14mu}{onto}\mspace{14mu} a}}} \\{{second}\mspace{14mu}{image}\mspace{14mu} 60{b.}}\end{matrix}$

Referring now to method 601 illustrated in FIG. 6c , for each post 30 ain image 60 a, hypothesize (step 602) that a post 30 a is at thehorizontal projection of barrier 30 onto the road surface. Eachhypothesis corresponding to one of linear image structures (H,I,J,K)translates to a different image vertical coordinate y1 (step 604) whichcan then be used to compute a forward distance Z1 and lateral distanceX1 (step 606). Given the known forward motion of host vehicle 18,horizontal image co-ordinate of a post 30 a can be used to compute (step610) the new horizontal image coordinate of the post (x2) in image 60 b.Only one hypothesis (J) gives a projection x2 that correctly aligns withone post 30 a in second image 60 b. Linear mark J is therefore a correcthypothesis for the true projection of barrier 30 a onto the road plane(step 612). A forward distances Z to post 30 a may be determined fromhost vehicle 18 based on the image motion and the forward motion of hostvehicle 18. The lateral distances X from the host vehicle to post 30 amay be computed from the forward distance and the horizontal imagecoordinate of post 30 a.

Reference is now also made to FIG. 6d , which illustrates an alternativemethod 603 to method 601. For multiple vertical structures or posts 30a, forward distance Z is computed (step 622) and from the forwarddistance and horizontal image coordinate, the lateral distances X arecomputed (step 624) for posts 30 a. Linear marks or linear imagestructure (H,I,J,K) may be assumed (step 626) to be hypothetical roadplane lines in the road plane at lateral distances X. However, only oneof linear marks (H,I,J,K) is actually in the road plane. Thehypothesized road plane lines at different lateral distances X may beprojected (step 628) onto an image of structural barrier 30 in imageframe 60 a. In image frame 60 b, the correct linear mark (H,I,J,K) ofthe hypothesized road plane lines is selected (step 630) by aligningwith the image of one of posts 30 a in image frame 60 b, according tothe image motion prediction responsive to the motion of vehicle 18.

In other words, the image motion of an image patch suspected to be theimage of part of a road barrier and the host vehicle motion are used tocompute the longitudinal distance (Z) and lateral distance (X) of thatpatch from host vehicle 18. The X,Ye,Z location is projected into theimage point p(x,y), where Ye is taken to be the height of the road planerelative to the camera 12. The patch is verified to be on barrier 30 bycorresponding p(x,y) to nearby linear image structures (H,I,J,K).

Posts 30 a are tracked sometimes with multiple possible image motionsfor the same post due to aliasing. Each motion gives a X,Z worldcoordinates for post 30 a. Post 30 a is projected onto the ground plane(by setting the Y coordinate to Yc). We now have X,Y,Z coordinates toproject into the camera image point p(x,y). Then it is verified if pointp(x,y) falls on or close to a linear image structure (H,I,J,K).

Reference is now made to FIGS. 7a and 7b which shows two images 70 a and70 b and FIG. 7c which shows a method 701 according to an aspect of thepresent invention. In images 70 a and 70 b, the image of barrier 32 hasan absence of a clearly detectable vertical structure unlike the imageprovided by barrier 30 and posts 30 a (shown in FIGS. 6a and 6b ).

The principle of method 701, is to ascertain if a patch in image(schematically shown by ellipse 76 a), on or bounded by a lineintersecting the lane vanishing point, is a patch on the road surface oran upright (substantially vertical) portion of road barrier 32. However,in image 70 a it is a challenge to decide if perhaps patch 76 a is roadsurface. A motion of texture in the patch as host vehicle 18 movesforward may uniquely determine whether the surface of the patch isupright and a part of barrier 32 or the road patch is on the roadsurface. If the patch is upright, all the points along columns in thepatch move together but scale vertically as shown by patch(schematically shown ellipse 76 b) in image frame 70 b. If the patch ison the road surface, then all points in rows of the patch will movetogether and scale horizontally. The motion of texture in the patch istypically large and the shape of the patch may change significantly.

Referring now also to method 701, patch 76 a is located (step 702). Theknown vehicle motion and the lateral distance (X) may be used to warp(step 706) image patch 76 a using two motion models. One motion modelassumes a vertical surface and the other motion model assumes a roadsurface. A matching score to next image 70 b using warped image 70 a isthen computed (step 708), allowing for some fine alignment to compensatefor inexact host vehicle 18 motion. The matching score can be Sum ofSquare Distance (SDD) or edge based (e.g. Hauussdorf distance). The bestmatching score in decision step 710 determines whether, the image patchis of a concrete barrier 32 at the lateral distance (X) given by thelane mark (step 712), or if the image patch is of road texture (step714).

In some cases, methods 601 and 701 may not give a reliable result everyimage frame 60/70. However, the road structure and presence of a barrier30, 32 persists over time. Therefore, a model for location of a barrier30, 32 may be accumulated over many image frames. Multiple hypothesesmay be maintained with only the hypotheses above a certain confidenceaffecting a warning and/or control system 23. Different warning systemsmay require different levels of confidence: automatic lane change wouldrequire almost 100% confidence that there is no barrier 30, 32. Whileinitiating early braking for collision mitigation might require amoderately high (90%) confidence that there is a barrier 30, 32. Earlytriggering of lane departure warning (LDW) 19 may require a lowerconfidence.

Multiframe analysis may allow and/or an exchange of information to/fromother driver assistance systems LDW 19, FCW 17 allows for theintegration of additional cues that might be less frequent. For example,a car passing on the left is a clear indication that there is no barrier30,32 on the left side. In method 701, lateral motion of host vehicle 18in the lane of travel may produce a looming effect. The looming effectmay be used to determine if the an upper line bounding patch 76 is infact at the same lateral distance as a lower line bounding patch 76indicating that patch 76 is part of a barrier 32 or if patch 76 is animage of an object farther away such as in the road or ground surface.

The indefinite articles “a” and “an” is used herein, such as “a patch”,“an image” have the meaning of “one or more” that is “one or morepatches” or “one or more images”.

Although selected embodiments of the present invention have been shownand described, it is to be understood the present invention is notlimited to the described embodiments. Instead, it is to be appreciatedthat changes may be made to these embodiments without departing from theprinciples and spirit of the invention, the scope of which is defined bythe claims and the equivalents thereof.

What is claimed is:
 1. A method for detection of a structural barrierextending along a road, the method performed by a driver assistancesystem mountable in a host vehicle, wherein the driver assistance systemincludes a camera operatively connectible to a processor, the methodcomprising: capturing a plurality of image frames in the forward fieldof view of the camera; and determining a first horizontal imagecoordinate, in a first frame of the plurality of image frames, of afeature of the structural barrier; determining a second horizontal imagecoordinate, in a second frame of the plurality of image frames, of thefeature of the structural barrier, wherein determining the secondhorizontal image coordinate includes identifying a change from the firsthorizontal image coordinate based on movement of the host vehicle,wherein the movement of the host vehicle is used to determine that thefeature of the structural barrier is upright; and identifying a linearimage structure, hypothesized based on the first frame, as a correctprojection of the structural barrier onto a road plane based on thelinear image structure correctly aligning with the feature in the secondframe.
 2. The method of claim 1, wherein the linear image structureincludes an image line on an image frame of the plurality of imageframes, and wherein the image line intersects a vanishing point of theimage frame.
 3. The method of claim 1, wherein the feature includes avertical post of the structural barrier.
 4. The method of claim 1,wherein the linear image structure is identified from a plurality ofhypothesized linear image structures.
 5. The method of claim 4, whereinthe linear image structure is the only linear image structure of theplurality of hypothesized linear image structures to correctly alignwith the feature in the second frame.
 6. The method of claim 4, whereineach of the plurality of hypothesized linear image structures correspondto different image vertical coordinates identified in the first frame.7. An electronic device mountable in a host vehicle for detection of astructural barrier extending along a road, the electronic devicecomprises: one or more processors; memory; a camera operativelyconnectible to the one or more processors; one or more programs, whereinthe one or more programs are stored in the memory and configured to beexecuted by the one or more processors, the one or more programsincluding instructions for: capturing a plurality of image frames in theforward field of view of the camera; determining a first horizontalimage coordinate, in a first frame of the plurality of image frames, ofa feature of the structural barrier; determining a second horizontalimage coordinate, in a second frame of the plurality of image frames, ofthe feature of the structural barrier, wherein determining the secondhorizontal image coordinate includes identifying a change from the firsthorizontal image coordinate based on movement of the host vehicle,wherein the movement of the host vehicle is used to determine that thefeature of the structural barrier is upright; and identifying a linearimage structure, hypothesized based on the first frame, as a correctprojection of the structural barrier onto a road plane based on thelinear image structure correctly aligning with the feature in the secondframe.
 8. The electronic device of claim 7, wherein the linear imagestructure includes an image line on an image frame of the plurality ofimage frames, and wherein the image line intersects a vanishing point ofthe image frame.
 9. The electronic device of claim 7, wherein thefeature includes a vertical post of the structural barrier.
 10. Theelectronic device of claim 7, wherein the linear image structure isidentified from a plurality of hypothesized linear image structures. 11.The electronic device of claim 10, wherein the linear image structure isthe only linear image structure of the plurality of hypothesized linearimage structures to correctly align with the feature in the secondframe.
 12. The electronic device of claim 10, wherein each of theplurality of hypothesized linear image structures correspond todifferent image vertical coordinates identified in the first frame. 13.A non-transitory computer-readable storage medium storing one or moreprograms for detection of a structural barrier extending along a road,the one or more programs comprising instructions, which when executed byone or more processors of an electronic device with a camera, cause thedevice to: capturing a plurality of image frames in the forward field ofview of the camera; determining a first horizontal image coordinate, ina first frame of the plurality of image frames, of a feature of thestructural barrier; determining a second horizontal image coordinate, ina second frame of the plurality of image frames, of the feature of thestructural barrier, wherein determining the second horizontal imagecoordinate includes identifying a change from the first horizontal imagecoordinate based on movement of the host vehicle, wherein the movementof the host vehicle is used to determine that the feature of thestructural barrier is upright; and identifying a linear image structure,hypothesized based on the first frame, as a correct projection of thestructural barrier onto a road plane based on the linear image structurecorrectly aligning with the feature in the second frame.
 14. Thecomputer-readable storage medium of claim 13, wherein the linear imagestructure includes an image line on an image frame of the plurality ofimage frames, and wherein the image line intersects a vanishing point ofthe image frame.
 15. The computer-readable storage medium of claim 13,wherein the feature includes a vertical post of the structural barrier.16. The computer-readable storage medium of claim 13, wherein the linearimage structure is identified from a plurality of hypothesized linearimage structures.
 17. The computer-readable storage medium of claim 16,wherein the linear image structure is the only linear image structure ofthe plurality of hypothesized linear image structures to correctly alignwith the feature in the second frame.
 18. The computer-readable storagemedium of claim 16, wherein each of the plurality of hypothesized linearimage structures correspond to different image vertical coordinatesidentified in the first frame.